3680 results about "Network connectivity" patented technology

A federated distributed computational system enables secure, privacy-preserving biological data analysis and engineering through interconnected nodes coordinated in a distributed graph architecture. A federation manager allocates resources, manages data flow and lineage, establishes privacy boundaries, and maintains cross-institutional knowledge relationships. Each node contains a processing unit for biological data analysis, privacy preservation protocols for secure multi-party computation, a knowledge graph structure with supporting data stores, and encrypted network connections. The federation manager enforces all computation and data exchange through secure channels while maintaining privacy, security, and contractual boundaries. This architecture enables research institutions to collaborate on complex biological analyses without compromising sensitive data, facilitating breakthrough discoveries through shared computational resources while maintaining strict data privacy and security controls.

The invention relates to a multi-protocol transmission text data monitoring and warning method and system, and the method comprises the steps: generating a multi-source protocol transmission instance based on dynamic authorization and hardware security verification, and collecting and analyzing text data; a network connection state, a data backlog amount and sensor numerical value content parameters are monitored in real time through multiple threads, and a transmission state and content exception event queue is generated; learning a causal relationship among network congestion, equipment faults and alarm events by using a Bayesian network algorithm, calculating a root cause probability in combination with a dynamic weight distribution strategy, and generating a comprehensive alarm list of priority ranking; on the basis of user feedback data, protocol weights and alarm strategies are adaptively updated, abnormal early warning triggering, data snapshot binding and closed-loop optimization of alarm logs are achieved, and the problems that in a multi-protocol mixed transmission scene, safety adaptability is poor, the monitoring dimension is single, root cause analysis depends on static rules, and strategy updating lags are solved. And the real-time performance, the accuracy and the self-adaptability of data transmission of the industrial Internet of Things are improved.

A federated distributed computational system enables secure, multi-institutional biological data analysis and genomic medicine through interconnected, decentralized nodes in a federated distributed graph architecture. A federation manager coordinates computational resource allocation, control and data flows, establishes privacy and security boundaries, implements multi-scale spatiotemporal analysis and simulation modeling, models cross-species or intrapopulation elements, and maintains cross-institutional knowledge relationships. Each node includes a local processing unit for biological data analysis, including multiomics and gene editing, privacy-preserving protocols for secure multi-party computation, a hierarchical knowledge graph for managing multi-domain biological relationships across spatial and temporal scales, and encrypted network connections. The system implements cross-species genetic analysis via phylogenetic integration, environmental response modeling through spatiotemporal tracking, and multi-scale tensor-based data integration with adaptive dimensionality control. This architecture enables research institutions to collaborate on complex biological analyses and genomic medicine applications while maintaining strict data privacy and security controls.

The invention relates to the technical field of intelligent power grids, in particular to an intelligent power distribution room sensing system and method based on data fusion. The multi-source data acquisition module is used for synchronously acquiring electrical parameters, mechanical vibration signals, temperature distribution data and environment monitoring data of power equipment in a power distribution room; the edge computing gateway is connected to the multi-source data acquisition module and is configured to perform time alignment, abnormal value elimination and feature extraction on the original sensing data; the data fusion analysis server is connected to the edge computing gateway through a network and comprises a space-time alignment unit used for unifying monitoring data of different sampling frequencies to the same time reference; the self-adaptive weight fusion unit is used for dynamically adjusting fusion weight according to the reliability of the data of each sensor; the state evaluation unit is used for generating an equipment health degree score and a fault early warning signal based on a fusion result; according to the scheme, monitoring blind areas and misjudgment risks caused by data islands can be fundamentally solved.

The invention provides a multi-level heterogeneous computing power network task scheduling and resource allocation method and system. In a computing power network, each hierarchical network is connected with an intelligent agent for task scheduling and resource allocation. In the training process, the intelligent agent obtains local observation information of the computing power node in the hierarchical network. And the intelligent agent aggregates and converts local observation information according to the relation feature map to generate a feature matrix and an adjacent matrix. Local feature embedding is calculated by using a graph convolutional network, and feature aggregation is carried out in combination with information of a cooperative agent to obtain a local embedding state; and the intelligent agent executes a joint action according to the local embedding state, wherein the joint action comprises task scheduling and resource allocation. And according to an execution result, the agent obtains a reward value and state information and stores the reward value and the state information into an experience playback buffer area. And sampling data from a buffer area, and updating a value function and strategy parameters by taking optimization of calculation task completion time and resource use efficiency as a target. And after a preset training round, obtaining a trained model. The resource overhead of information interaction can be reduced, and the scheduling efficiency is improved.

Methods, systems, and computer-readable storage media for receiving, from probes, probe data indicative of vulnerabilities of one or more devices to cybersecurity threats. The devices are connected over a network. Aggregated probe data is generated by mapping the probe data using data relationships obtained from a relational database, The data relationships define vulnerability types of cybersecurity threats. A cybersecurity compliance score of each of the one or more devices is determined using a correlation of the aggregated probe data to cybersecurity status scenarios defining consequences related to the cybersecurity threats. A cybersecurity assessment report including the compliance score of the one or more devices and an action plan preventing the consequences related to the cybersecurity threats are provided.

A video gateway system at a worksite is coupled to multiple cameras on a network, and backs-up video streams generated by the cameras to a backend cloud backup video storage system and a frontend (cache) video storage system. The video gateway system generates an aggregated video asset from a plurality of streams of video from the multiple cameras, and generates metadata and a backup report associated with the video asset. The video asset, metadata, and backup report are stored on the backend cloud backup video storage system in an file system, and are also stored on the frontend (cache) video storage system such that for at least a period of time, the video asset and the associated the metadata and backup report are stored on both the cloud backup video storage system, facilitating quick access and retrieval to the stored video for retrieval for streaming, activity detection, and other uses.

The present invention discloses an integrated circuit chip with an address code, a key, and a mechanical keyboard. The integrated circuit chip contains a programmable address code, integrates a magnetic induction circuit, a GRB magic color drive circuit, and includes a power pin, a ground pin, and a data pin. The power pins of n integrated circuit chips are connected in parallel to share a power network VCC, the ground pins are connected in parallel to share a ground network GND, and the data pins are connected in parallel to share a data line network DIO connected to an MCU, and data information is transmitted on the data line network DIO. Another integrated circuit chip with an address code only requires a power network VCC and a ground network GND, and data information is modulated and transmitted on the power network, which greatly saves wiring space, reduces the difficulty of PCB design, and exponentially reduces the number of electronic components. In addition, a variety of different customized code sending methods and working modes are provided, making its application simpler, more efficient, and more reliable.

A computer-readable storage medium stores instructions for execution by one or more processors of a UE to configure the UE for simultaneous connection with a 5G NR network and at least a second network, and to cause the UE to perform operations. The operations include encoding UE capability information for transmission to a base station. The UE capability information indicates the UE supports MUSIM operations. First RRC signaling received from the base station includes a plurality of MUSIM configurations to configure the UE for the MUSIM operations. Interference between at least one of the plurality of MUSIM configurations and operation of the UE on the at least second network is detected. Second RRC signaling is transmitted, which indicates a temporary UE capability restriction based on the interference.

The invention relates to a method and a system for automatically updating an intelligent gateway and synchronizing a server. The method comprises the following steps: carrying out system self-inspection and network connection verification on the intelligent gateway to obtain network state information; obtaining version information of the intelligent gateway according to the network state information, and performing local storage management to obtain an update request data packet; establishing a secure communication connection with an OTA server based on the update request data packet to obtain a session credential; performing version comparison of multi-objective optimization by using the session voucher, and executing intelligent update decision making to obtain an update execution plan; downloading an update file from the OTA server according to the update execution plan and performing integrity verification to obtain a verified firmware image file; and deploying the verified firmware image file to the standby partition and executing update installation to complete state synchronous feedback. According to the method, the adaptability and accuracy of the update decision are improved, dynamic resource scheduling in the update process is realized, and the update is ensured to be carried out in the optimal system state.

The invention relates to the technical field of unmanned systems, and discloses an unmanned ship directional operation system cooperating with unmanned aerial vehicle cruise, and the system comprises an unmanned aerial vehicle module which carries a high-precision sensor and is used for scanning a water area environment in real time and generating a high-precision map; the unmanned ship module is provided with a navigation system and an operation device and is used for executing water surface orientation operation according to the high-precision map; the cloud platform module is connected with the unmanned aerial vehicle module and the unmanned ship module through a wireless communication network and is used for data interaction, task scheduling and remote control; and the intelligent charging shore base is used for providing automatic charging support for the unmanned ship module. A high-precision water area map is generated in real time through the unmanned aerial vehicle module and is transmitted to the unmanned ship module, so that the unmanned ship can optimize the route and the obstacle avoidance operation according to the dynamically updated environment data, and the task execution precision is remarkably improved; therefore, the effectiveness of patrolling, cleaning and monitoring tasks is improved.

The invention discloses a macro server system, an application method, electronic equipment and a storage medium, and relates to the technical field of computers, physical devices (equipment components) of the macro server system are modularly designed to be combined into modules with different functions, and the physical devices support hot plugging, so that the physical devices can be conveniently and quickly combined into modules with different functions. Meanwhile, a plurality of physical devices are connected through a high-speed communication network to form a distributed module cluster, so that a large number of computing resources, management resources and network resources can be packaged into an independent server environment, and the limitation of a current server in the aspects of processor performance, bandwidth, physical structure, hardware quantity, firmware resources and the like is solved; according to the technical scheme, the macro server system capable of supporting large-scale data processing, high-concurrency access and complex operation is constructed, so that the technical problem of how to improve the performance and expandability of the server can be solved, and the technical effect of constructing the macro server system capable of supporting large-scale data processing, high-concurrency access and complex operation is achieved.

The invention discloses an ultrasonic image off-line acquisition and dynamic synchronous processing method and system, which realizes off-line acquisition and dynamic synchronous processing of an ultrasonic image under the condition of network interruption through six functional modules, namely a network state monitoring module, an online data synchronization module, an image acquisition processing module, an off-line mode switching module, an off-line diagnosis processing module and an increment synchronization module. The method comprises the following steps: acquiring network connection state data and judging a working mode; pulling and caching tasks and template data in an online state; obtaining multi-modal image data and performing double-writing storage; detecting network interruption and switching to an offline mode; performing AI analysis on the images acquired offline and generating a report; and detecting network recovery and executing incremental data synchronization. According to the invention, the problem of service interruption caused by dependence of a traditional PACS system on a network is solved, the network adaptability and robustness of the system are improved, the operation and maintenance cost is reduced, and the system fault recovery time is shortened.

The invention provides a power transmission line small target detection method based on improved YOLOv5s, and the method comprises the steps: constructing a small target detection model, training the small target detection model, and detecting a small target on a power transmission line through the trained model. The model comprises an input end, a backbone network, a connection layer and a prediction layer, wherein the input end adopts Mosaic data enhancement; the backbone network introduces inverse operation of sub-pixel convolution to perform down-sampling; the connection layer integrates multi-head self-attention and shift window attention, enhances the modeling capability of a long-distance target, optimizes multi-scale feature extraction by adopting a bidirectional feature fusion strategy, and improves the detection precision of a small target; and the prediction layer adopts an improved CIoULoss loss function. Compared with the prior art, the small target in the power transmission line can be identified more accurately, false detection and missing detection are reduced, the detection robustness in a complex environment is improved, and the method is suitable for application scenes such as unmanned aerial vehicle inspection and power equipment monitoring.

The invention discloses a photovoltaic power station operation data monitoring method and system, and relates to the technical field of photovoltaic power station equipment monitoring, and the method comprises the steps: collecting equipment operation parameters to form an original data set; constructing an equipment association network by taking the equipment as a node; based on the data set and the association network, time sequence collaborative change and correlation analysis are carried out on the equipment parameters, and a collaborative change model is established; judging that equipment is abnormal through a model, and calling same-type parameters of directly connected nodes to form a to-be-verified set; in combination with the network connection edge weight, calculating the influence degree of the associated parameters on the abnormal equipment by applying a dynamic weight evaluation algorithm, and generating a priority list; and performing iterative optimization on the collaborative change model according to the priority list, and outputting a monitoring report. The system comprises a data acquisition module, a network construction module, an analysis modeling module, an anomaly judgment module, a weight evaluation module, a model optimization module, a data storage module and the like to realize abnormal associated factor identification and monitoring logic optimization.

To provide a mechanism capable of easily searching for information indicating a file storage location without being restricted by circumstances under which the file has been stored on a network.SOLUTION: A user terminal 101, which can be connected via a network 105 to a large language model server 103 in which a large language model searches for URLs being information indicating file storage locations on the basis of similarity of language vectors of natural language, comprises a CPU 201 that transmits, in natural language, a query sentence for inquiring about a file storage location to the large language model, and receives, from the large language model, a response sentence that conveys a URL being information indicating the file storage location searched by the large language model using a language vector of the natural language of the query sentence.SELECTED DRAWING: Figure 1

Devices in a wireless communication system perform methods related to a GNSS position fix procedure. A user equipment connected to a network entity via a non-terrestrial network receives a measurement gap configuration and an indication of a remaining-validity-duration-update triggering condition. The UE conducts a GNSS position fix procedure for estimating a UE position during a measurement gap according to the measurement gap configuration. When the GNSS position fix procedure is successfully completed, the UE transmits a remaining GNSS validity duration. When the remaining-validity-duration-update triggering condition is met, the UE transmits an updated remaining GNSS validity duration.

The invention discloses an ad hoc network communication system without a signal area, particularly relates to the technical field of wireless communication, and is used for solving the problem that a connectivity critical state caused by node density or mobility change in a low-density network is not fully considered in an existing dynamic routing protocol. The network connectivity critical state is pre-judged by acquiring node position coordinates and communication radiuses in real time and combining the average node spacing and the dispersion in the moving direction; screening a high-priority detection node based on an obstacle avoidance cooperative angle variance and a virtual pheromone concentration in a critical state, and adaptively adjusting a detection message sending frequency according to a node moving speed; constructing a path stability evaluation model by fusing the link survival duration, the node residual energy and the signal intensity fluctuation rate, dynamically screening a high-stability path as a main transmission link, and taking the rest lists as standby links; and monitoring the signal fluctuation characteristics of the main link in real time, and quickly switching to the path with the optimal comprehensive stability in the standby link in an abnormal state.

The invention relates to a notebook software vulnerability scanning method based on a security policy. According to the method, firstly, a security policy library of a target notebook is obtained, and the security policy library comprises access control rules, data operation limiting conditions and vulnerability detection reference requirements for different software types; collecting software running data of the target notebook computer, wherein the software running data comprises current running process information, file system operation records, network connection states and software configuration parameters; performing matching analysis on the software operation data and the security policy library to generate a preliminary scanning result; evaluating the risk level of the software vulnerability according to the preliminary scanning result; and finally, based on the risk level and the repair guide terms in the security policy library, generating software vulnerability repair guide information. Therefore, notebook software vulnerabilities can be scanned comprehensively and accurately, and effective repair guidance is provided.

The invention discloses a tumor space-occupying brain network neural image alignment method based on multi-modal fusion, and belongs to the technical field of medical image processing and artificial intelligence crossing. The method comprises the following core steps of multi-modal image heterogeneous feature decoupling, tumor occupation deformation field modeling, functional network topological structure maintenance, cross-modal feature adversarial alignment, dynamic deformation constraint optimization and clinical interpretability verification, and construction of a three-dimensional non-rigid registration network based on a double attention mechanism. And differential homeomorphic mapping of a tumor focus area and normal brain tissue is realized through the cascaded spatial transformation module. Aiming at the problems of insufficient multi-modal feature alignment and brain network topology distortion in the prior art, the invention provides a function connection constrained cross-modal fusion strategy, a graph convolution network is adopted to encode resting state function connection features, and network node displacement caused by tumor occupation is dynamically corrected in combination with deformable convolution and a bidirectional feature competition mechanism; a space consistency loss function based on white matter fiber bundle tracing is designed, and through diffusion tensor imaging feature guide structure-function bimodal joint optimization, the problems of insufficient registration precision in a focus area and whole brain network connection distortion of a traditional method are solved. Experiments show that the registration precision of the method in glioma cases reaches 0.82 mm and is improved by 37% compared with that of a traditional method, and dissection-function consistency of functional network reconstruction around tumors is remarkably improved.

A computer system retrieves provisioning data and observability data (metrics, logs, events, alerts, inventory) for a plurality of components from remote servers. The computer system extracts component identifiers from the provisioning data and the log data. The computer system identifies relationships between components from the provisioning data and the log data, such as environmental variable relationships, network relationships, session relationships, access relationships, and network connection relationships. The computer system generates a topology in which nodes represent components and edges represent relationships. The topology is updated to show changes to components and relationships. A user may interact with a visual representation of the topology to change data displayed or invoke changes to the components and relationships represented by the topology.

A system for an automated real-time fraud detection based on predictive analytics of call data including a processor of a call analysis server (CAS) node configured to host a machine learning (ML) module and connected to at least one user-entity node over a network and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: capture user call data including a plurality of key elements from the at least one user-entity node; parse the user call data to extract a plurality of classifying features based on the plurality of key elements; query a local calls database to retrieve local historical calls-related data based on the plurality of classifying features; generate at least one feature vector based on the plurality of classifying features and the local historical calls-related data; provide the at least one feature vector to the ML module coupled to an Artificial Neural Network (ANN); receive a plurality of user call ranking parameters from a call predictive model generated by the ML module using outputs of the ANN based on the feature vector; and generate a fraud verdict for the user call based on the plurality of call ranking parameters.

The invention provides a multi-core GPU cache division method, architecture and data access method, relates to the technical field of graphics processor design, and aims to realize cross-core access performance system-level optimization and improve the performance of processing large-scale image data by introducing a cache allocation mechanism based on topology awareness. The method comprises the steps that a multi-core-grain GPU topological structure comprising a target computing core grain and at least one associated computing core grain is obtained, a to-be-divided far-end data cache of the target computing core grain is used for caching image data from a far-end video memory, and the to-be-divided far-end data cache is connected with the associated computing core grain through an inter-core-grain interconnection network; if the number of the calculation core particles contained in the multi-core-particle GPU does not exceed a first preset threshold value, the inter-core-particle hop count between each associated calculation core particle and a target calculation core particle is determined based on the topological structure, and then the corresponding capacity of the associated calculation core particles in the to-be-divided cache of the target calculation core particle is determined; and dividing the to-be-divided cache according to the capacity corresponding to each associated calculation core particle.

Disclosed in the present application are a data processing method based on a large language model, and a large language model, an electronic device, a computer-readable storage medium and a computer program product. The method is applied to a user terminal, wherein a large language model is deployed on the user terminal, and weight parameters of linear calculation layers of the large language model are pre-quantized into format data of an integer data type. The method comprises: acquiring input data; performing vector conversion on the input data by means of an embedding layer of a large language model, so as to obtain a floating-point query vector of a floating-point data type corresponding to the input data; converting the floating-point query vector into an integer query vector of an integer data type; and performing an operation by means of weight parameters of linear calculation layers and the integer query vector, so as to obtain a query result corresponding to the input data. By means of the solution provided in the present application, a large language model can be smoothly run on a user terminal, such that the user terminal can provide services for users without needing network connectivity, and can better ensure the privacy of the users.

The invention relates to the technical field of network switching, in particular to a heterogeneous network dual-mode self-adaptive switching method and system. According to the method, the multi-dimensional environment sensing data and the initial signal intensity are acquired, the signal intensity is calibrated in a dynamic environment, the dynamic response of the network state to real-time change is realized, and the connection state characteristic and the side network consumption index of the dual-mode network are acquired by combining the calibrated signal intensity. The switching demand can be evaluated on the basis of the data, the switching demand can be judged more accurately through the multi-dimensional evaluation mechanism, the limitation that a traditional method only depends on signal strength is avoided, and the switching demand can be evaluated by generating an optimized directed time sequence graph and a network performance data set. According to the technical scheme, the equipment can make a scientific and reasonable switching decision according to the real-time network state snapshot data and the preset optimization time sequence graph, and the connection requirements of the equipment can be dynamically adapted under the variable network conditions, so that the optimal network experience is kept, and the network connection quality is improved.

Provided are an information processing apparatus and method for providing a monetary mechanism for providing an online interview. 【Solution means】In an information processing system in which an information processing apparatus, a plurality of service terminals, and a plurality of store terminals are connected to a network, the information processing apparatus 3 includes an acquisition unit 331 that acquires a service ID from the store terminal 2, an interview processing unit 332 that executes processing for conducting an online interview between the store terminal 2 and the service terminal 1, a first determination unit 334 that refers to a first condition management database and determines a service charge based on a first condition associated with the service ID corresponding to the interview conducting business operator, a second determination unit 335 that refers to a second condition management database and determines a store charge based on the second condition, and a charge processing unit 336 that executes processing for billing the service charge to the interview conducting business operator and executes processing for paying the store charge to the store business operator of the store or processing for billing the store business operator of the store.

A system to protect an asset includes a plurality of monitoring nodes each generating a data stream of current monitoring node values in time-domain. An anomalous space data source stores sets of anomalous feature vectors for each of the plurality of monitoring nodes generated by an anomaly detection model. A current system function processor, coupled to the plurality of monitoring nodes over a network, receives receive data streams from each of the plurality of monitoring nodes, and generates a set of current feature vectors. An anomaly detection computer coupled to the plurality of monitoring nodes receives the data streams from the plurality of monitoring nodes and the set of anomalous feature vectors, and outputs at least one decision boundary based on processing, using the anomaly detection model, of the current feature vectors relative to the sets of anomalous feature vectors.

The invention discloses a weak network environment photographing off-line uploading method and system, and relates to the technical field of file upload, and the method comprises the steps: monitoring the network bandwidth and the use conditions of a CPU and a memory in real time, building a dynamic calculation model, and achieving the adaptive adjustment of the size of a data block; dividing the file to be uploaded into blocks of which the sizes are pre-adjusted according to a dynamic blocking algorithm, and storing the blocks locally; according to a priority calculation model, establishing a dynamic priority queue, and calculating a priority for each block uploading task; a queue scheduler is set, high-priority blocks are ensured to be preposed, a priority queue is established, the queue is reordered at set time intervals, and high-priority block tasks are ensured to be preposed; the network connection state is detected in real time, the dynamic change of the network quality is continuously monitored, the time period when the network condition meets the preset condition is intelligently identified according to the monitoring result, and locally cached blocks are timely uploaded to a service system in an offline mode according to the priority. According to the invention, the file can be uploaded according to the network state.

The invention discloses a permanent magnet synchronous motor temperature monitoring method based on digital-analog hybrid drive, and the method specifically comprises the steps: dividing a motor into a plurality of heat source nodes, including a stator winding, a stator tooth part, a rotor core and the like, connecting the nodes through a thermal resistance and thermal capacity network, building a thermal network model of the motor, and carrying out the thermal network model; calculating the initial values of thermal resistance and thermal capacity of each component of the motor, and optimizing parameters in a thermal network model by using a differential evolution algorithm based on the lumped parameter thermal network model and in combination with a data-driven strategy. Furthermore, temperature rise prediction is dynamically adjusted according to motor state data (such as stator current, rotating speed and the like) collected in real time so as to realize real-time temperature estimation. The method is high in temperature estimation precision, does not affect the performance of the motor, is simple in calculation, is good in real-time performance, and has physical interpretability. The temperature rise of the motor can be predicted in real time under different working conditions, early warning is given out, motor faults caused by too high temperature rise are effectively avoided, and the reliability and safety of the motor are improved.

The invention relates to the technical field of unmanned aerial vehicle anti-collision path planning, in particular to an unmanned aerial vehicle ad hoc network anti-collision path planning method based on a graph neural network, and the method comprises the steps: obtaining the topographic data of a task airspace, recording the initial positions, target positions and motion constraint conditions of all unmanned aerial vehicles, and constructing unmanned aerial vehicle graph structure data; according to the unmanned aerial vehicle graph structure data, taking each unmanned aerial vehicle as a unit node, and representing a potential collision relationship between two adjacent unmanned aerial vehicles by a side between the nodes; initializing features of the nodes and the edges, and completing training of an unmanned aerial vehicle graph neural network model based on the input features of the nodes and the edges as input of the preset unmanned aerial vehicle graph neural network model; and performing collision risk prediction based on the unmanned aerial vehicle graph neural network model, and generating and outputting an optimal flight path. According to the invention, through the graph neural network and multi-objective optimization, intelligent cooperative flight of the unmanned aerial vehicle group is realized, the collision risk and energy consumption are significantly reduced, and the network connectivity and task efficiency are ensured at the same time.